Successful business operations typically require efficient management of numerous physical assets (buildings, equipment, and appliances). These physical assets consume a multitude of resources such as electricity, gas, and water. Increasingly, these physical assets are being transformed into “cyber physical systems” (CPS) via addition of smart meters, sensors, and networked monitoring devices. This has resulted in a deluge of data about asset behavior and performance becoming available, however, requisite tools to analyze and leverage these data for improving asset performance are currently unavailable.
One approach to improve asset performance is to monitor the assets over time, to pro-actively identify those requiring maintenance, to detect inefficient operation, or to detect those assets that are being improperly controlled. Timely detection of inefficient performance of physical assets has been identified as being able to save around 15 to 30% of energy in commercial buildings. However, there are a number of various factors that can impact the performance of physical assets in a building. As such, it is often challenging to detect if the performance of the physical assets is efficient or not, especially if the functionalities of the physical assets have not deteriorated in a way that current monitoring techniques are able to identify.